Update configs

1 files changed, 51 insertions, 38 deletions

diff --git a/training/conf/experiment/vqgan.yaml b/training/conf/experiment/vqgan.yaml
index 98f3346..726757f 100644
--- a/training/conf/experiment/vqgan.yaml
+++ b/training/conf/experiment/vqgan.yaml
@@ -1,18 +1,26 @@
+# @package _global_
+
 defaults:
   - override /network: vqvae
   - override /criterion: null
   - override /model: lit_vqgan
-  - override /callbacks: wandb_vae
+  - override /callbacks: vae
   - override /optimizers: null
   - override /lr_schedulers: null
 
+epochs: &epochs 100
+ignore_index: &ignore_index 3
+num_classes: &num_classes 58
+max_output_len: &max_output_len 682
+summary: [[1, 1, 576, 640]]
+
 criterion:
-  _target_: text_recognizer.criterions.vqgan_loss.VQGANLoss
+  _target_: text_recognizer.criterion.vqgan_loss.VQGANLoss
   reconstruction_loss:
     _target_: torch.nn.BCEWithLogitsLoss
     reduction: mean
   discriminator:
-    _target_: text_recognizer.criterions.n_layer_discriminator.NLayerDiscriminator
+    _target_: text_recognizer.criterion.n_layer_discriminator.NLayerDiscriminator
     in_channels: 1
     num_channels: 64
     num_layers: 3
@@ -21,39 +29,35 @@ criterion:
   discriminator_factor: 1.0
   discriminator_iter_start: 8.0e4
 
+mapping: &mapping
+  mapping:
+    _target_: text_recognizer.data.mappings.emnist.EmnistMapping
+    extra_symbols: [ "\n" ]
+
 datamodule:
-  batch_size: 12
-  # resize: [288, 320]
-  augment: false
+  _target_: text_recognizer.data.iam_extended_paragraphs.IAMExtendedParagraphs
+  batch_size: 4
+  num_workers: 12
+  train_fraction: 0.9
+  pin_memory: true
+  << : *mapping
 
 lr_schedulers:
-  generator:
-    _target_: torch.optim.lr_scheduler.OneCycleLR
-    max_lr: 3.0e-4
-    total_steps: null
-    epochs: 64
-    steps_per_epoch: 1685
-    pct_start: 0.3
-    anneal_strategy: cos
-    cycle_momentum: true
-    base_momentum: 0.85
-    max_momentum: 0.95
-    div_factor: 25.0
-    final_div_factor: 10000.0
-    three_phase: true
+  network:
+    _target_: torch.optim.lr_scheduler.CosineAnnealingLR
+    T_max: *epochs
+    eta_min: 1.0e-5
     last_epoch: -1
-    verbose: false
-    interval: step
+    interval: epoch
     monitor: val/loss
  
-#   discriminator:
-#     _target_: torch.optim.lr_scheduler.CosineAnnealingLR
-#     T_max: 64
-#     eta_min: 0.0
-#     last_epoch: -1
-# 
-#     interval: epoch
-#     monitor: val/loss
+  discriminator:
+    _target_: torch.optim.lr_scheduler.CosineAnnealingLR
+    T_max: *epochs
+    eta_min: 1.0e-5
+    last_epoch: -1
+    interval: epoch
+    monitor: val/loss
 
 optimizers:
   generator:
@@ -75,11 +79,20 @@ optimizers:
     parameters: loss_fn.discriminator
 
 trainer:
-  max_epochs: 64
-  # limit_train_batches: 0.1
-  # limit_val_batches: 0.1
-  # gradient_clip_val: 100
-
-# tune: false
-# train: true
-# test: false
+  _target_: pytorch_lightning.Trainer
+  stochastic_weight_avg: false
+  auto_scale_batch_size: binsearch
+  auto_lr_find: false
+  gradient_clip_val: 0
+  fast_dev_run: false
+  gpus: 1
+  precision: 16
+  max_epochs: *epochs
+  terminate_on_nan: true
+  weights_summary: null
+  limit_train_batches: 1.0 
+  limit_val_batches: 1.0
+  limit_test_batches: 1.0
+  resume_from_checkpoint: null
+  accumulate_grad_batches: 2
+  overfit_batches: 0